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Abstract:

Implementing intelligent agent services includes generating an
ontological domain for an individual based upon sets of information
elements. A set of the information elements represents aspects of a
detectable behavior of the individual at a point in time. The detectable
behavior is one of a number of detectable behaviors of the individual
occurring within a physical and virtual geography and in relation to
time. The detectable behaviors include an activity conducted by the
individual at a computer and a presence of the individual at a function.
Implementing the intelligent agent services also includes determining
relevance of relationships among the sets of the information elements in
the ontological domain, and searching sources of information using the
sets of the information elements having a relationship determined to be
relevant, and identifying a solution for satisfying an interest based on
the search.

Claims:

1. A method for implementing intelligent agent services, comprising:
generating, via a computer, an ontological domain for an individual based
upon a plurality of sets of information elements, wherein a set of the
information elements represents aspects of a detectable behavior of the
individual at a point in time, the detectable behavior comprising one of
a number of detectable behaviors of the individual occurring within a
physical and virtual geography and in relation to time, the detectable
behaviors including an activity conducted by the individual at a computer
and a presence of the individual at a function; determining, via the
computer, relevance of relationships among the plurality of sets of the
information elements in the ontological domain, wherein a relationship
determined to be relevant is identified as an interest of the individual;
and searching sources of information using the plurality of sets of the
information elements having the relationship determined to be relevant,
and identifying a solution for satisfying the interest responsive to the
searching, the solution having a relationship to the activity conducted
at the computer and the presence of the individual at the function.

2. The method of claim 1, wherein the generating includes creating
subdomains of contextually organized collections of the plurality of sets
of the information elements, the subdomains including any orthogonally
related data identified among the detectable behaviors.

3. The method of claim 1, further comprising: formatting the solution
into a message; and presenting the message to a device associated with
the individual.

4. The method of claim 1, wherein the searching sources of information
further comprises: creating a search string from the plurality of sets of
the information elements; gathering data in response to the searching
using the search string, and comparing the data to the plurality of sets
of the information elements; identifying matches between the data and the
plurality of sets of the information elements; and analyzing the matches
to determine the solution.

5. The method of claim 2, further comprising: dynamically updating the
ontological domain over time by iteratively gathering the information
elements in response to continuous detection of behaviors of the
individual, and updating the subdomains to reflect the iteratively
gathering; and updating the interest based upon updates made to the
ontological domain.

6. The method of claim 1, further comprising: storing each of the
plurality of sets of information elements in a corresponding record using
a standard data structure having corresponding data fields, the record
including a unique identifier; and storing records produced for each of
the plurality of sets of the information elements in a database; and
creating subdomains of the ontological domain that include orthogonally
related data by identifying matching information elements from data
fields across multiple records in the database via corresponding unique
identifiers.

7. The method of claim 1, wherein the presence of the individual at the
function is determined by a cellular network and device in combination
with the activity conducted by the individual at the computer.

8. A system for implementing intelligent agent services, comprising: a
host system computer; and an application executing on the host system
computer, the application implementing: generating an ontological domain
for an individual based upon a plurality of sets of information elements,
wherein a set of the information elements represents aspects of a
detectable behavior of the individual at a point in time, the detectable
behavior comprising one of a number of detectable behaviors of the
individual occurring within a physical and virtual geography and in
relation to time, the detectable behaviors including an activity
conducted by the individual at a computer and a presence of the
individual at a function; determining relevance of relationships among
the plurality of sets of the information elements in the ontological
domain, wherein a relationship determined to be relevant is identified as
an interest of the individual; and searching sources of information using
the plurality of sets of the information elements having the relationship
determined to be relevant, and identifying a solution for satisfying the
interest responsive to the searching, the solution having a relationship
to the activity conducted at the computer and the presence of the
individual at the function.

9. The system of claim 8, wherein the generating includes creating
subdomains of contextually organized collections of the plurality of sets
of the information elements, the subdomains including any orthogonally
related data identified among the detectable behaviors.

10. The system of claim 8, wherein the application further implements:
formatting the solution into a message; and presenting the message to a
device associated with the individual.

11. The system of claim 8, wherein the searching sources of information
further comprises: creating a search string from the plurality of sets of
the information elements; gathering data in response to the searching
using the search string, and comparing the data to the plurality of sets
of the information elements; identifying matches between the data and the
plurality of sets of the information elements; and analyzing the matches
to determine the solution.

12. The system of claim 9, wherein the application further implements:
dynamically updating the ontological domain over time by iteratively
gathering the information elements in response to continuous detection of
behaviors of the individual, and updating the subdomains to reflect the
iteratively gathering; and updating the interest based upon updates made
to the ontological domain.

13. The system of claim 8, wherein the application further implements:
storing each of the plurality of sets of information elements in a
corresponding record using a standard data structure having corresponding
data fields, the record including a unique identifier; and storing
records produced for each of the plurality of sets of the information
elements in a database; and creating subdomains of the ontological domain
that include orthogonally related data by identifying matching
information elements from data fields across multiple records in the
database via corresponding unique identifiers.

14. A computer program product for implementing intelligent agent
services, the computer program product including instructions embodied on
a computer storage medium which when executed by a computer cause the
computer to implement a method, the method comprising: generating an
ontological domain for an individual based upon a plurality of sets of
information elements, wherein a set of the information elements
represents aspects of a detectable behavior of the individual at a point
in time, the detectable behavior comprising one of a number of detectable
behaviors of the individual occurring within a physical and virtual
geography and in relation to time, the detectable behaviors including an
activity conducted by the individual at a computer and a presence of the
individual at a function; determining relevance of relationships among
the plurality of sets of the information elements in the ontological
domain, wherein a relationship determined to be relevant is identified as
an interest of the individual; and searching sources of information using
the plurality of sets of the information elements having the relationship
determined to be relevant, and identifying a solution for satisfying the
interest responsive to the searching, the solution having a relationship
to the activity conducted at the computer and the presence of the
individual at the function.

15. The computer program product of claim 14, wherein the generating
includes creating subdomains of contextually organized collections of the
plurality of sets of the information elements, the subdomains including
any orthogonally related data identified among the detectable behaviors.

16. The computer program product of claim 14, wherein the instructions
further cause the computer to implement: formatting the solution into a
message; and presenting the message to a device associated with the
individual.

17. The computer program product of claim 14, wherein the searching
sources of information further comprises: creating a search string from
the plurality of sets of the information elements; gathering data in
response to the searching using the search string, and comparing the data
to the plurality of sets of the information elements; identifying matches
between the data and the plurality of sets of the information elements;
and analyzing the matches to determine the solution.

18. The computer program product of claim 15, wherein the instructions
further cause the computer to implement: dynamically updating the
ontological domain over time by iteratively gathering the information
elements in response to continuous detection of behaviors of the
individual, and updating the subdomains to reflect the iteratively
gathering; and updating the interest based upon updates made to the
ontological domain.

19. The computer program product of claim 14, wherein the instructions
further cause the computer to implement: storing each of the plurality of
sets of information elements in a corresponding record using a standard
data structure having corresponding data fields, the record including a
unique identifier; and storing records produced for each of the plurality
of sets of the information elements in a database; and creating
subdomains of the ontological domain that include orthogonally related
data by identifying matching information elements from data fields across
multiple records in the database via corresponding unique identifiers.

20. The computer program product of claim 14, wherein the presence of the
individual at the function is determined by a cellular network and device
in combination with the activity conducted by the individual at the
computer.

Description:

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation of U.S. patent application Ser.
No. 12/543,546, filed Aug. 19, 2009. The Ser. No. 12/543,546 application
is a continuation application of U.S. patent application Ser. No.
11/314,614, filed Dec. 20, 2005, the entire contents of each of which are
incorporated herein by reference.

BACKGROUND

[0002] The present invention relates generally to automated data
collection and processing, and more particularly, to methods, systems,
and computer program products for implementing ontological domain and
contextually intelligent agent services.

[0003] Information is ubiquitously created and exchanged using a variety
of communications technologies and systems. Various techniques have been
employed to capture and organize information in a way that facilitates
quick and simple retrieval and subsequent utilization. Intelligent
devices, or artificial intelligence devices, have been developed for
attempting to codify specific information about a discipline, or domain,
which can then be used for a variety of purposes.

[0004] In addition, collaborative filtering techniques have been used to
aggregate similar information sets from multiple individuals and provide
a summary opinion. Another technique has employed ontologically related
systems for allowing domain experts to create ontologies that can be used
for drawing inferences. However, these pre-defined domains do not reflect
the personalized needs, interests, or preferences of people at an
individual level. Nor do these domains dynamically change over time as
the preferences or interests of an individual change.

[0005] What is needed, therefore, is a way to address the individual
preferences, interests, and needs of individuals by automatically
collecting individual-specific information and generating customized
ontological domains for use in analysis and inferences. What is also
needed is a way to identify and present specific solutions that address
the needs, preferences, and interests of individuals.

BRIEF SUMMARY

[0006] Exemplary embodiments include methods for implementing intelligent
agent services. A method includes generating, via a computer, an
ontological domain for an individual based upon sets of information
elements. A set of the information elements represents aspects of a
detectable behavior of the individual at a point in time. The detectable
behavior is one of a number of detectable behaviors of the individual
occurring within a physical and virtual geography and in relation to
time. The detectable behaviors include an activity conducted by the
individual at a computer and a presence of the individual at a function.
The method also includes determining, via the computer, relevance of
relationships among the sets of the information elements in the
ontological domain, searching sources of information using the plurality
of sets of the information elements having the relationship determined to
be relevant, and identifying a solution for satisfying an interest in
response to the searching. The solution has a relationship to the
activity conducted at the computer and the presence of the individual at
the function.

[0007] Additional embodiments include a system for implementing
intelligent agent services. The system includes a host system computer
and an application executing on the host system computer. The application
performs a method that includes generating an ontological domain for an
individual based upon sets of information elements. A set of the
information elements represents aspects of a detectable behavior of the
individual at a point in time. The detectable behavior is one of a number
of detectable behaviors of the individual occurring within a physical and
virtual geography and in relation to time. The detectable behaviors
include an activity conducted by the individual at a computer and a
presence of the individual at a function. The method also includes
determining relevance of relationships among the sets of the information
elements in the ontological domain, searching sources of information
using the plurality of sets of the information elements having the
relationship determined to be relevant, and identifying a solution for
satisfying an interest in response to the searching. The solution has a
relationship to the activity conducted at the computer and the presence
of the individual at the function.

[0008] Further embodiments include a computer program product for
implementing intelligent agent services. The computer program product
includes instructions embodied on a computer storage medium, which when
executed by a computer cause the computer to implement a method. The
method includes generating an ontological domain for an individual based
upon sets of information elements. A set of the information elements
represents aspects of a detectable behavior of the individual at a point
in time. The detectable behavior is one of a number of detectable
behaviors of the individual occurring within a physical and virtual
geography and in relation to time. The detectable behaviors include an
activity conducted by the individual at a computer and a presence of the
individual at a function. The method also includes determining relevance
of relationships among the sets of the information elements in the
ontological domain, searching sources of information using the plurality
of sets of the information elements having the relationship determined to
be relevant, and identifying a solution for satisfying an interest in
response to the searching. The solution has a relationship to the
activity conducted at the computer and the presence of the individual at
the function.

[0009] Other systems, methods, and/or computer program products according
to embodiments will be or become apparent to one with skill in the art
upon review of the following drawings and detailed description. It is
intended that all such additional systems, methods, and/or computer
program products be included within this description, be within the scope
of the present invention, and be protected by the accompanying claims.

BRIEF DESCRIPTION OF DRAWINGS

[0010] Referring now to the drawings wherein like elements are numbered
alike in the several FIGURES:

[0011] FIG. 1 depicts a system upon which the ontological domain and
intelligent agent services may be implemented in exemplary embodiments;

[0012] FIG. 2 is a flow diagram describing a process for implementing the
ontological domain services in exemplary embodiments;

[0013] FIG. 3 is a data structure including sample data fields for storing
information elements and creating records for use in implementing the
ontological domain services in exemplary embodiments;

[0014] FIG. 4 is a database of records created using the data structure
depicted in FIG. 3 in exemplary embodiments;

[0015] FIG. 5 is a record illustrating a sample ontological domain used in
implementing the ontological domain services in exemplary embodiments;

[0016] FIG. 6 is a sample notification that includes an interest resulting
from implementation of the ontological domain services in exemplary
embodiments;

[0017] FIG. 7 is a flow diagram describing a process for implementing the
intelligent agent services in exemplary embodiments; and

[0018] FIG. 8 is a sample notification that includes content resulting
from the implementation of the intelligent agent services in exemplary
embodiments.

[0019] The detailed description explains the exemplary embodiments,
together with advantages and features, by way of example with reference
to the drawings.

DETAILED DESCRIPTION

[0020] In accordance with exemplary embodiments, ontological domain and
contextually intelligent agent services are provided. Information
elements for detectable behaviors are gathered and an ontological domain
is defined that reflects the information elements in terms of
transactions, locations, queries, and other behavioral indicators that
occur within a physical and/or virtual geography and in relation to time.
The ontological domain may be considered to be a contextual organization
of an information domain around a concept. Detectable behaviors may
include any type of activity, presence, transaction, etc., that is
capable of being detected by a human and/or machine.

[0021] The ontological domain is self-governing and may include one or
more domain categories, or sub-domains that provide an information
structure that enables orthogonally related elements among the
sub-domains to be ascertained and utilized. An interest can be determined
from analyzing the ontological domain. An interest may include any type
of information that is determined to be of value or relevance to a
particular individual. An interest may also include a need of the
individual. An identified interest may be used by the contextually
intelligent agent services to identify and search sources of information
for addressing the interest. The intelligent agent services look for
matches among information elements found within the information sources
and information elements relating to the interest. Any matches are
analyzed in order to determine a likely solution to the interest. The
solution is then made available to the relevant individual or entity. The
ontological domain services are described in FIGS. 1-6 and the
intelligent agent services are described in FIGS. 1, 5, and 7-8.

[0022] Turning now to FIG. 1, a system upon which the ontological domain
and intelligent agent services may be implemented in accordance with
exemplary embodiments will now be described. The system of FIG. 1
includes a host system 102 in communication with devices 110, 112, and
116, as well as information sources 104, 106, and 108 via one or more
networks 117. Host system 102 may be implemented by a service provider of
the ontological domain and intelligent agent services described herein.
For example, host system 102 may be operated by a network service
provider that provides Internet, Web, cable television, telephone, or
other similar type of services to customers, in addition to the
ontological domain and intelligent agent services. Alternatively, host
system 102 may be implemented by an application service provider (ASP) or
other service enterprise.

[0023] In exemplary embodiments, information sources 104, 106, and 108
include a merchant 104, a financial institution 106, and a web server
information source 108. Merchant 104 may be a `brick and mortar` entity
that provides products and/or services to customers at a geographic
location (e.g., a local hardware store, a grocery market, a gas station,
a retail chain establishment, etc.). Additionally, or alternatively,
merchant 104 may be a `virtual` establishment that provides goods and/or
services over a network via, e.g., a website.

[0024] Financial institution 106 refers to a bank, credit union, or other
entity that provides financial services (e.g., checking/savings accounts,
loans, mortgages, investments, credit services, etc.) to customers.
Financial institution 106 may be a `brick and mortar` facility and/or a
virtual establishment, similar to the merchant 104 described above.

[0025] In exemplary embodiments, Web server source 108 refers to a network
entity that provides information (e.g., in response to requests, queries,
searches, etc.) to requesting individuals. Web server source 108 includes
server software executing on a processor and a data store with network
connectivity and may provide access to information in its data store via
a web site or portal to individuals. An example of an information source
implemented by Web server source 108 is a Web Log or BLOG established for
users in a BLOG community or a personal website maintained and operated
by an individual. Alternatively, web server source 108 may include
websites that provide information such as link directories, white papers,
reference libraries, etc.

[0026] The information sources described above are provided for
illustrative purposes. It will be appreciated that any number and type of
information sources that provide electronic information, products, and/or
services may be utilized in implementing the exemplary embodiments
described herein.

[0027] In exemplary embodiments, a mobile communications device 110, a
user system 112, a financial instrument 114, and a global positioning
system (GPS) device 116 are also included in the system of FIG. 1. Each
of these items 112-116 may be under the control of an individual or
entity (e.g., a business). Mobile communications device 110 may be a
cellular telephone, personal digital assistant (PDA), pager, laptop, or a
hybrid device that utilizes various communications technologies (e.g.,
digital wireless and over-the-air) technologies.

[0028] The user system 112 refers to a personal computer or desktop device
that is network-enabled via, e.g., digital subscriber line (DSL),
dial-up, or other similar type of networking systems and services. User
system 112 may execute applications, such as a web browser, word
processing tool, messaging application, etc.

[0030] GPS device 116 may be located in an automobile (not shown), a
mobile device (e.g., device 110), or other object.

[0031] In exemplary embodiments, host system 102 is in communication with
a storage device 122, which is also included in the system of FIG. 1.
Storage device 122 stores a variety of information including, e.g.,
information element records, ontological domains, notifications and agent
messages (also referred to herein as "publications") as will be described
further herein. Storage device 122 may be implemented using a variety of
devices for storing electronic information. It will be understood that
the storage device 122 may be implemented using memory contained in the
host system 102 or may be a separate physical device. The storage device
122 is logically addressable as a consolidated data source across a
distributed environment that includes network(s) 117. Information stored
in the storage device 122 may be retrieved and manipulated via the host
system 102.

[0032] The host system 102 depicted in FIG. 1 may be implemented using one
or more servers operating in response to a computer program stored in a
storage medium accessible by the server(s). The host system 102 may
operate as a network server (e.g., a web server) to communicate with the
information sources 104, 106, and 108, mobile communications device 110,
user system 112, and GPS device 116. The host system 102 handles sending
and receiving information to and from these devices and can perform
associated tasks. The host system 102 may also include a firewall to
prevent unauthorized access to the host system 102 and enforce any
limitations on authorized access. For instance, an administrator may have
access to the entire system and have the authority to modify portions of
the system. A firewall may be implemented using conventional hardware
and/or software as is known in the art.

[0033] The host system 102 may also operate as an application server. The
host system 102 executes one or more computer programs to provide
ontological domain and intelligent agent services. As shown in the system
of FIG. 1, host system 102 is executing an ontological domain (OD)
application 118 for implementing the ontological domain services, as well
as an agent application 120 for implementing the intelligent agent
services. Processing may be shared by other network entities (e.g.,
information sources 104-108, and/or devices 110, 112, 114, 116 and the
host system 102 by providing an application (e.g., java applet) to these
systems. Alternatively, these systems can include stand-alone software
applications for performing a portion of the processing described herein.
As previously described, it is understood that separate servers may be
utilized to implement the network server functions and the application
server functions.

[0034] Furthermore, the host system 102 may be integral with one of the
devices 110, 112, 114, or 116. In this example, the OD application 118
and the agent application 120 would be embedded or enabled by one of
those devices 110, 112, 114, or 116 without the need for a separate host
system 102. A single device 110, 112, 114, or 116 would therefore be
capable not only of detecting and communicating information but also of
acting on that information through the OD application 118 and the agent
application 120 which are resident on that device 110, 112, 114, or 116.
As an example, consider an individual hiking on a mountain with a device
110. The device 110 may be able to detect the altitude, the GPS location
of the individual, and receive weather information that warns of
impending severe weather conditions. The device 110 may also have
obtained information on a tent previously purchased by the individual and
the purchase of a cabin rental. The OD application 118 detects a need for
the individual to take protective action and the agent application 120
provides possible solutions, such as immediately going back down the
mountain to the cabin or information on how and where to pitch the tent
to be protected from the elements. In addition to having the host system
102, which includes the OD application 118 and agent application 120,
resident on one of the devices 110, 112, 114, or 116, the host system 102
may reside on multiple of the devices 110, 112, 114, or 116 and/or the
processing of the OD application 118 and the agent application 120 may be
shared among devices 110, 112, 114, or 116.

[0035] The network(s) 117 may be any type of known networks including, but
not limited to, a wide area network (WAN), a local area network (LAN), a
global network (e.g. Internet), a virtual private network (VPN), an
intranet, or a combination thereof. The network(s) 117 may be implemented
using wireless network technologies or any kind of physical network
implementation known in the art. Mobile communications device 110, user
system 112, GPS device 116, and/or the host system 102 may be connected
to the network(s) 117 in a wireless fashion.

[0036] Turning now to FIG. 2, a process for implementing the ontological
domain services will now be described in accordance with exemplary
embodiments. The ontological domain services provide a mechanism for
automating the collection of information that is derived from detectable
behaviors. These behaviors may be conducted via any of devices 110, 112,
114, and 116 and/or via any of information sources 104, 106 and 108. At
step 202, host system 102 receives information elements from a source.
The information source of these elements may be one or more of mobile
communications device 110, user system 112, GPS device 116, or any of
information sources 104, 106, and 108. For example, the detectable
behavior might be an individual accessing a website of a travel agency
(e.g., merchant 104) via user system 112 and, using financial instrument
114 to purchase a reservation at a hotel. A set of information elements
that may be produced by this behavior may include the name, address, and
phone number of the individual ordering the reservation, the name of the
hotel, the date of the reservation, the cost of the room, the method of
payment (e.g., account number, card issuer, etc.), the name and
identification (e.g., website address) of the travel agent, and other
similar types of information elements. Much, if not all, of this
information is easily captured during the purchase/order transaction.

[0037] A record of the transaction from which these information elements
may be extracted is typically handled by the financial institution (e.g.,
106) that processes the charge on behalf of the individual, the merchant
(e.g., 104) via a reservation confirmation, and/or the individual via an
electronic sales receipt transmitted, e.g., via email to the individual
at the user system 112. Because much of this information may be
confidential, the host system 102 providing the ontological domain
services may establish a trusted relationship with specified sources of
information in order to protect the identity of the individual and/or the
privacy information contained in these information elements. The trusted
relationship may include secure channels of communication (via e.g.,
encryption, virtual private networking technologies, and other tools for
protecting confidential information).

[0038] In another example, the detectable behavior may be the presence of
the individual in a geographic location. If the individual carries a
cellular telephone (e.g., mobile communications device 110), the
detectable behavior may include the presence of the individual in a
specific location (e.g., cell) that is detected by a servicing cell
tower, whereby the individual's cellular telephone communicates a signal
to the cell tower, which in turn, notifies the host system 102 (either
via the cellular telephone itself or directly). The set of information
elements may include the identification of the location, the date, time
and/or duration of the presence in the location, or other types of
information.

[0039] A similar type of detectable behavior may be the location of the
individual using GPS device 116. The detectable behavior may be acquired
via the device 116, which sends a signal to a satellite, and which in
turn, provides the location information to the host system 102 or
directly to the device (e.g., automobile) that is carrying the GPS device
116. These information elements are collected by the ontological domain
application 118 over a period of time (e.g., days, weeks, months, etc.).

[0040] In another example, a detectable behavior may be the presence of an
individual at a particular function, e.g., a road race. The information
elements may be derived from a combination of sources, such as a
registration to participate in the event via a website and GPS
information derived from the individual's presence at the event. The
information elements produced from the website registration may include
the nature of the function (e.g., road race), and the date and time of
the event. The relationships between the registration information (e.g.,
date, time, and function), coupled with the GPS information (e.g., the
location of the individual at the same date and time noted in the
registration) provide a full picture of the behavior.

[0041] Returning now to FIG. 2, the ontological domain application 118
filters the set of information elements and selects primary terms and/or
tags from these elements at step 204. This may be accomplished, for
example, by eliminating commonly occurring words, such as "a", "the",
"an", "or", etc. from the information set. The primary terms and/or tags
may be captured and stored in a record using a standardized construct or
data structure and corresponding data fields at step 206. A sample data
structure 300 is shown in FIG. 3. The data fields include a RECORD
IDENTIFIER that may be used to uniquely identify a particular record
which, in turn, stores a set of information elements. Each record may
include multiple behaviors that may simultaneously occur at a given point
in time. Other data fields provided in data structure 300 will be
described in more detail in FIG. 4.

[0042] Turning now to FIG. 4, a database of records (including sample
data) produced using the data structure 300 of FIG. 3 will now be
described in accordance with exemplary embodiments. Database 400 of FIG.
4 includes multiple records that are identified in column 402A and stored
in chronological order in the database 400. As shown in database 400, the
records span a time period from Dec. 1, 2005 through Mar. 1, 2006 (column
402B). The time periods provided in column 402B reflect the date of the
occurrence of the corresponding behavior. Likewise, the time column 402C
indicates a time of the occurrence of the corresponding behavior. Each
row in database 400 reflects a record. The data fields capturing the
filtered information elements are shown as 402B-402I. Thus, for example,
an individual frequented Anna's Market at 9:00 a.m. on Dec. 1, 2005.
Anna's Market is located on Main Street. The individual purchased bread
at the market for $5.00. The filtered information elements, or primary
terms, from this activity are stored in the first Record of database 400.

[0043] As indicated above, multiple behaviors may be detected for a single
activity or behavior. While only two columns are shown in database 400
(e.g., column 402F and 402G) to reflect a single behavior, it will be
appreciated that additional columns may be provided in database 400 to
reflect these multiple behaviors. It will also be appreciated that
information elements may be acquired from a behavior that do not neatly
fall into the specific columns or data fields provided in database 400.
An OTHER column 402H provides flexibility in enabling additional
descriptive information elements to be captured. For example, Record 2
illustrates that an individual purchased a Mercedes® automobile and
within this purchase transaction, the current mileage of the vehicle is
captured and stored in the record. Column 402I reflects a VALUE column
that enables a value to be entered that corresponds to the nature of the
behavior. For example, the cost of the vehicle in the second record is
provided in the value column 402I, while the duration of a web search is
provided in the value column 402I of Record 8 of database 400. Other
values may be indicated in column 402I, e.g., cost savings.

[0044] Turning back to FIG. 2, the application 118 creates an ontological
domain at step 208 using the records produced in step 206, a sample of
which is shown in FIG. 5. The ontological domain application 118
linguistically assembles the collected information into sub-domains that
are categorized using an arbitrarily formed and self-organized
classification scheme. In other words, the ontological domain is not
pre-defined by a "domain expert" but is dynamically created, defined, and
refined over time based upon newly collected information and an analysis
engine or component of the ontological domain application 118.

[0045] As shown in FIG. 5, the ontological domain includes sub-domains
502-510, namely, AUTO 502, TRAVEL 504, RECREATION 506, BIRDS 508, and
HOME 510. Each sub-domain provides a contextually-organized collection of
information elements using, e.g., a topical index produced from the
behaviors. Each sub-domain, therefore, is customized according to the
particular behaviors of an individual or actuator. For example, a shown
in FIG. 5, sub-domain 510 includes a collection of home-related
information elements that are grouped by topic (e.g., the individual's
home). Note that the elements provided in sub-domain 510 reflect the
behaviors produced and tracked, in part, in Records 4, 6, and 8-10 of
database 400. Likewise, detectable behaviors used in collecting elements
for sub-domain 502 may include, e.g., purchasing a car (Record 2),
servicing the car, purchasing gasoline, and enrolling in an automobile
servicing program.

[0046] Returning to FIG. 2, the ontological domain is analyzed by the
ontological domain application 118. The analysis may be implemented using
various combinations of search strings (e.g., concatenating two or more
data fields 402B-402I) and searching the records for patterns, frequency,
etc., that indicate one or more relationships among the elements. In
addition, or alternatively, the analysis may include some pre-defined
logic for assisting in the analysis. The analysis may include determining
the relevance of each of the information elements based upon measurable
aspects, e.g., quantity, frequency, costs, redundancy, history, relative
location, time, duration, value, or a combination thereof at step 210.
The relevance of these information elements may be determined by applying
weights using these aspects in order to ascertain the significance of
these behaviors at step 212. The analysis is useful in understanding the
potential importance or significance of the information elements to the
individual. These relevance determinations may change over time as new
behaviors are detected and analyzed.

[0047] Potential relationships among elements between sub-domains are
determined at step 214 and any relevance of these relationships. For
example, using the ontological domain 500 of FIG. 5, suppose that
sub-domain 502 reflects that the mileage on the individual's car is
20,000 as reflected by the service history (which also reflects that the
last servicing was 3 months ago at the time of purchase). Suppose also,
that the sub-domain 504 reflects that the individual booked a trip to a
hotel in Vermont in March of 2006 (as shown in Record Y1 of database 400
of FIG. 4). Also suppose that the distance between the individual's
residence and the hotel in Vermont is 200 miles. This distance may be
acquired by acquiring the location of the individual's residence from
sub-domain 510 and calculating the distance between the locations using,
e.g., a mapping tool). The ontological domain application 118 analyzes
the elements within these sub-domains in order to assess any
relationships among them. The analysis results in a relationship between
the sub-domains 502, 504, and 510 with respect to the automobile, the
recreation, and the residence, respectively. The relationships determined
among the sub-domain elements may result in a proposed or predicted
interest for the individual at step 216; namely, the automobile may need
to be serviced if a trip to Vermont is imminent. As shown in FIG. 2, this
analysis is a looping process (step 214 returns to step 208) in order to
account for newly acquired information.

[0048] At step 218, the ontological domain application 118 may publish the
results of the analysis for the benefit of the individual. The individual
may access the results in a number of ways. For example, the results may
be formatted into a message format. A sample message 600 is shown and
described in FIG. 6. The message 600, or notification, may be transmitted
to the individual via network(s) 117, e.g., as an email, telephone
communication, text message, or other means. The message 600 may be
stored on any of devices 110, 112, or 116.

[0049] As indicated above, contextual intelligent agent services are also
provided by the host system 102. The intelligent agent services are
implemented via agent application 120 executing on the host system 102
and provide a mechanism for enabling automated intelligent agents to
acquire and synthesize disparate types of information from a variety of
information sources, and to present relevant and useful information to
respective individuals, entities, and/or servicing agents that request
these services. The intelligent agent services may be facilitated using
information collected about an individual and/or by information directly
provided by the individual. Alternatively, or in addition, the
intelligent agent services may be facilitated using information acquired
from one or more ontological domains (e.g., from the interest resulting
from the process described in FIG. 2).

[0050] Turning now to FIG. 7, a process for implementing the intelligent
agent services will now be described in accordance with exemplary
embodiments. At step 702, an interest is identified. As indicated above,
the agent application 120 may receive this information, e.g., directly
from an individual in the form of a request or it may be ascertained
using, e.g., the results of the analysis performed on an ontological
domain (e.g., domain 500). For example, suppose there is an interest in
finding a vacation destination that is suitable for a family of four
during the month of July.

[0051] The agent application 120 utilizes an agent that creates a search
string at step 703 from the information elements and searches for
information sources (e.g., information sources 104-108 of FIG. 1) that
may potentially address the interest at step 704. This may be performed
using various techniques, such as searching a database of information
sources using key word search techniques (e.g., key words that reflect,
identify, or describe the interest). A commercial search engine may be
employed for identifying information sources as well. In addition,
information sources may not be entirely electronic sources of
information, but rather may be a combination of electronic, human, and/or
mechanical sources of information. Using the above example, the search
string used in the search may include [vacation+tourist
attractions+July+family friendly+hotel+airline], etc. In addition, if the
agent application 120 utilizes an ontological domain (e.g., domain 500)
for the individual in this request, additional information elements may
be inferred for this key word search, e.g., children's ages, residence of
family from sub-domain 510 (e.g., in order to determine the nearest
airport), interests (e.g., sub-domain 506 and 508 elements), etc.

[0052] Once one or more information sources are identified, the agent
gathers information elements from these one or more sources via
communications transmission technologies including, e.g., Rich Site
Summary (RSS), File Transfer Protocol (FTP), BitTorrent, etc. at step
706. The information gathered may be formatted using a standardized data
structure similar to the one shown and described in FIG. 3.

[0053] At step 708, the information elements gathered in step 706 are
compared with information elements associated with the interest in order
to identify any matches. At step 710, it is determined whether any
matches have been found. If not, the process returns to step 706 where
information continues to be gathered. Otherwise, the agent application
120 determines if the matches exceed a threshold at step 711. If so, the
search string is modified at step 712 and the flow returns to step 706.
The threshold is provided in order to ensure that only the most relevant
information is returned (e.g., too many results may indicate that the
search string is too broad and would not provide useful, relevant
information).

[0054] If, however, the matches do not exceed the threshold at step 711,
the intelligent agent application 120 analyzes the matches at step 714.
The analysis may include determining the relevance of the information
elements in a manner similar to that described in step 212 of FIG. 2
(e.g., by using the threshold criteria).

[0055] At step 716, the agent application 120 uses the results of the
analysis to determine whether a solution exists for satisfying the
interest (i.e., whether there is at least one relevant match). If not,
the process returns to step 712 whereby a new search string (broadened)
is generated for the agent. Otherwise, the match is formatted for
publication at step 720. The solution, or match, may be represented as an
agent message, or publication, a sample of which is shown and described
in FIG. 8. Using the above example, the message may include a list of
vacation destinations. As shown in a sample message 800 of FIG. 8,
solutions are organized in a topical format, namely, CRUISES, ADVENTURE
TRAVEL, and BEST DEALS 802. The user selects BEST DEALS, which causes a
sub-window 804 to be presented. As shown in sub-window 804, the
individual is presented with two options, "Busch Gardens, Fla." and New
York City, N.Y.". The solution may include choices of hotels that provide
a discount based upon the time of travel, the ages of the children, and
the method of payment, to name a few. In addition, the solution for Busch
Gardens reflects the interests of the individual (i.e., an event
featuring an exhibit of exotic birds corresponding to sub-domain 508 of
FIG. 5). The solution for New York City reflects the interests of the
individual (i.e., Metropolitan Museum of Art exhibit in July
corresponding to sub-domain 506 of FIG. 5).

[0056] In exemplary embodiments, the intelligent agent application 120 may
initiate multiple agents for generating multiple searches, each of which
relate to a specific interest. Thus, at any given time there may be many
agents actively searching for information solutions to specified
interests associated with a single individual.

[0057] In addition, exemplary embodiments may offer a service plan that
enables individuals to request development and maintenance of
personalized ontological domains, e.g., for a servicing fee. The
ontological domain services may provide services based upon time (e.g.,
per month), number of interests per individual, or other criteria.
Furthermore, the same or independent service provider may provide
intelligent agent services to individuals using similar service plan
criteria (e.g., per month, number of interests), or may be structured
around a number of agents employed.

[0058] As indicated above, the ontological domain and intelligent agent
services provide an automated, self-governing tool for collecting and
processing information elements as a result of detectable behaviors, and
anticipating an interest as a result. The intelligent agent services also
facilitate the search and acquisition of relevant information in
anticipation of an interest, or in response to a request for a solution
for an interest.

[0059] As described above, the exemplary embodiments can be embodied in
the form of computer-implemented processes and apparatuses for practicing
those processes. The exemplary embodiments can also be embodied in the
form of computer program code containing instructions embodied in
tangible media, such as floppy diskettes, CD ROMs, hard drives, or any
other computer-readable storage medium, wherein, when the computer
program code is loaded into and executed by a computer, the computer
becomes an apparatus for practicing the embodiments. The exemplary
embodiments can also be embodied in the form of computer program code,
for example, whether stored in a storage medium, loaded into and/or
executed by a computer, or transmitted over some transmission medium,
such as over electrical wiring or cabling, through fiber optics, or via
electromagnetic radiation, wherein, when the computer program code is
loaded into an executed by a computer, the computer becomes an apparatus
for practicing the embodiments. When implemented on a general-purpose
microprocessor, the computer program code segments configure the
microprocessor to create specific logic circuits.

[0060] While the invention has been described with reference to exemplary
embodiments, it will be understood by those skilled in the art that
various changes may be made and equivalents may be substituted for
elements thereof without departing from the scope of the invention. In
addition, many modifications may be made to adapt a particular situation
or material to the teachings of the invention without departing from the
essential scope thereof. Therefore, it is intended that the invention not
be limited to the particular embodiments disclosed for carrying out this
invention, but that the invention will include all embodiments falling
within the scope of the claims. Moreover, the use of the terms first,
second, etc. do not denote any order or importance, but rather the terms
first, second, etc. are used to distinguish one element from another.
Furthermore, the use of the terms a, an, etc. do not denote a limitation
of quantity, but rather denote the presence of at least one of the
referenced item.